{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "PROBER = \"TCPIP0::192.168.0.2::800::SOCKET\"\n",
    "SMU = \"GPIB0::17::INSTR\"\n",
    "SWITCH = \"GPIB0::22::INSTR\"\n",
    "\n",
    "import pyvisa\n",
    "rm = pyvisa.ResourceManager()\n",
    "\n",
    "prober = rm.open_resource(PROBER)\n",
    "prober.read_termination = '\\r\\n'\n",
    "B1500a = rm.open_resource(SMU)\n",
    "B2201 = rm.open_resource(SWITCH)\n",
    "rm.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#prober stage\n",
    "prober.query(\"*IDN?\")\n",
    "prober.write(\"move_chuck_contact\")\n",
    "prober.write(\"move_chuck_separation\")\n",
    "#prober.write(\"map:step_first_die\")\n",
    "prober.write(\"map:step_next_die\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "PROBER = \"TCPIP0::192.168.0.2::800::SOCKET\"\n",
    "\n",
    "\n",
    "import pyvisa\n",
    "rm = pyvisa.ResourceManager()\n",
    "\n",
    "prober = rm.open_resource(PROBER)\n",
    "prober.read_termination = '\\r\\n'\n",
    "\n",
    "prober.write(\"map:step_next_die\")\n",
    "\n",
    "prober.close()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 开关矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "SWITCH = \"GPIB0::22::INSTR\"\n",
    "\n",
    "import pyvisa\n",
    "rm = pyvisa.ResourceManager()\n",
    "B2201 = rm.open_resource(SWITCH)\n",
    "\n",
    "#switching matrix\n",
    "import B2200\n",
    "import time\n",
    "#1,1234-1234\n",
    "#2,1234-5678\n",
    "#3,1234-9-12\n",
    "#4,openall\n",
    "B2200.Load_Path(B2201,1)\n",
    "#time.sleep(2)\n",
    "#B2200.Load_Path(B2201,2)\n",
    "#time.sleep(2)\n",
    "#B2200.Load_Path(B2201,3)\n",
    "#time.sleep(2)\n",
    "#B2200.Load_Path(B2201,4)\n",
    "\n",
    "rm.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "B1500a.query(\"*IDN?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 单个器件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NMOS-DIE-20240814_140301-201p-outter"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#b1500a smu\n",
    "def transCurve(DeviceType = 'P',ADC='AIT 1,2,1',direction='Single Linear',reverse=False,points=101):\n",
    "    PROBER = \"TCPIP0::192.168.0.2::800::SOCKET\"\n",
    "    SMU = \"GPIB0::17::INSTR\"\n",
    "    SWITCH = \"GPIB0::22::INSTR\"\n",
    "\n",
    "    if DeviceType == 'P':\n",
    "        startV, endV, Vds, chnSource = -2, 0.5, -2, '1'\n",
    "    elif DeviceType == 'N':\n",
    "        startV, endV, Vds, chnSource = 2, -0.5, 2, '4'\n",
    "    if reverse:\n",
    "        startV,endV = endV,startV\n",
    "\n",
    "    import pyvisa\n",
    "    rm = pyvisa.ResourceManager()\n",
    "\n",
    "    B1500a = rm.open_resource(SMU)\n",
    "    B1500a.write('*RST')\n",
    "    B1500a.write('CN')\n",
    "\n",
    "    #--------------------IV_Sweep函数测试参数示例（双变量扫描）------------------#\n",
    "    Unit1='3'                     #扫描变量1对应的物理端口为4\n",
    "    VName1='VGate'                   #扫描变量1的名字为VD，注意电压模式的端口命名为V....,电流模式端口命名为I...\n",
    "    Direction1=direction    #扫描变量1的方向为Double，并且加电压模式为Linear（更多模式见34）\n",
    "    Start1=startV                   #扫描变量1的起始电压为-3 V\n",
    "    end1=endV                     #扫描变量1的终止电压为3 V\n",
    "    nop1=points                      #扫描变量1的点数目为201（Double的话，实际数据点为201*2）\n",
    "    Comp1=1e-2                  #扫描变量1的限流值\n",
    "    range1='Auto'         #扫描变量1的测量Range\n",
    "\n",
    "    VAR_setup=[Unit1,VName1,Direction1,Start1,end1,nop1,Comp1,range1] #打包扫描变量，如果单变量扫描，不用第二行\n",
    "\n",
    "    Measurement_setup = []\n",
    "\n",
    "    Unit='2'                    #测量变量1的物理端口为\n",
    "    VName='VDrain'                  #测量变量1的名称，注意测电流是固定电压名称为V...，测电压是固定电流，名称是I...\n",
    "    VorI=Vds                 #测量变量1的固定电压为0 V\n",
    "    Comp=0.1                 #测量变量1的限流值\n",
    "    range='Auto'                #测量变量1的Range\n",
    "    Measurement_setup  += [Unit,VName,VorI,Comp,range] #打包测量变量，有几个打包几个\n",
    "\n",
    "    Unit=chnSource                   #测量变量1的物理端口为\n",
    "    VName='VSource'                  #测量变量1的名称，注意测电流是固定电压名称为V...，测电压是固定电流，名称是I...\n",
    "    VorI=0                 #测量变量1的固定电压为0 V\n",
    "    Comp=0.1                  #测量变量1的限流值\n",
    "    range='Auto'                #测量变量1的Range\n",
    "    Measurement_setup  += [Unit,VName,VorI,Comp,range] #打包测量变量，有几个打包几个\n",
    "\n",
    "\n",
    "    #print(Measurement_setup)\n",
    "    B1500a.timeout = 60000\n",
    "    B1500a.write('*RST')\n",
    "    B1500a.write('CN 1,2,3,4')\n",
    "    import B1500\n",
    "    res = B1500.IV_sweept(B1500a,VAR_setup,Measurement_setup,ADC=ADC)#AIT 1,2,1 20ms 1,1,125 10ms\n",
    "\n",
    "    import pandas\n",
    "    df = pandas.DataFrame(res[1:],columns=['GateV','GateI','DrainV','DrainI','SourceV','SourceI'],dtype=float)\n",
    "    B1500a.close()\n",
    "    rm.close()\n",
    "    return df\n",
    "from matplotlib import pyplot as plt \n",
    "import numpy as np\n",
    "\n",
    "def timemap(tstr):\n",
    "    l = tstr.split(',')\n",
    "    if l[1]=='1':\n",
    "        return str(0.08*int(l[2]))+'ms'\n",
    "    else:\n",
    "        return str(20*int(l[2]))+'ms'\n",
    "\n",
    "n=1\n",
    "for i in range(n):\n",
    "    for point in [51,101,201]:\n",
    "        for reverse in [False,True]:\n",
    "            for tp in ['P','N']:\n",
    "                #True False\n",
    "                df = transCurve(tp,ADC='AIT 1,2,1',points=point,reverse=reverse)\n",
    "                plt.plot(df['GateV'],abs(df['SourceI']),label=f'{tp}SourceI')\n",
    "                #plt.plot(df['GateV'],abs(df['DrainI']),label=f'{tp}DrainI')\n",
    "                plt.yscale('log')\n",
    "                from datetime import datetime\n",
    "                tStamp = datetime.strftime(datetime.now(),\"%Y%m%d_%H%M%S\")\n",
    "                df.to_excel(f\"./result/{tp}MOS-DIE-p3-{tStamp}-{point}p-{'out' if reverse else 'center'}.xlsx\",sheet_name='Data')\n",
    "                print(f\"\\r{tp}MOS-DIE-{tStamp}-{point}p-{'out' if reverse else 'center'}\",end='')\n",
    "\n",
    "#plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NMOS-DIE-20240807_153022-5s-50.0ms"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#b1500a smu\n",
    "def transCurve(DeviceType = 'P',\n",
    "               ADC='AIT 1,2,1',\n",
    "               direction='Single Linear',\n",
    "               reverse=False,\n",
    "               points=101,\n",
    "               t_hold=0.0,s_delay=0.0,t_delay=0.0):\n",
    "    PROBER = \"TCPIP0::192.168.0.2::800::SOCKET\"\n",
    "    SMU = \"GPIB0::17::INSTR\"\n",
    "    SWITCH = \"GPIB0::22::INSTR\"\n",
    "\n",
    "    if DeviceType == 'P':\n",
    "        startV, endV, Vds, chnSource = -2, 0.5, -2, '1'\n",
    "    elif DeviceType == 'N':\n",
    "        startV, endV, Vds, chnSource = 2, -0.5, 2, '4'\n",
    "    if reverse:\n",
    "        startV,endV = endV,startV\n",
    "\n",
    "    import pyvisa\n",
    "    rm = pyvisa.ResourceManager()\n",
    "\n",
    "    B1500a = rm.open_resource(SMU)\n",
    "    B1500a.write('*RST')\n",
    "    B1500a.write('CN')\n",
    "\n",
    "    #--------------------IV_Sweep函数测试参数示例（双变量扫描）------------------#\n",
    "    Unit1='3'                     #扫描变量1对应的物理端口为4\n",
    "    VName1='VGate'                   #扫描变量1的名字为VD，注意电压模式的端口命名为V....,电流模式端口命名为I...\n",
    "    Direction1=direction    #扫描变量1的方向为Double，并且加电压模式为Linear（更多模式见34）\n",
    "    Start1=startV                   #扫描变量1的起始电压为-3 V\n",
    "    end1=endV                     #扫描变量1的终止电压为3 V\n",
    "    nop1=points                      #扫描变量1的点数目为201（Double的话，实际数据点为201*2）\n",
    "    Comp1=1e-2                  #扫描变量1的限流值\n",
    "    range1='Auto'         #扫描变量1的测量Range\n",
    "\n",
    "    VAR_setup=[Unit1,VName1,Direction1,Start1,end1,nop1,Comp1,range1] #打包扫描变量，如果单变量扫描，不用第二行\n",
    "\n",
    "    Measurement_setup = []\n",
    "\n",
    "    Unit='2'                    #测量变量1的物理端口为\n",
    "    VName='VDrain'                  #测量变量1的名称，注意测电流是固定电压名称为V...，测电压是固定电流，名称是I...\n",
    "    VorI=Vds                 #测量变量1的固定电压为0 V\n",
    "    Comp=0.1                 #测量变量1的限流值\n",
    "    range='Auto'                #测量变量1的Range\n",
    "    Measurement_setup  += [Unit,VName,VorI,Comp,range] #打包测量变量，有几个打包几个\n",
    "\n",
    "    Unit=chnSource                   #测量变量1的物理端口为\n",
    "    VName='VSource'                  #测量变量1的名称，注意测电流是固定电压名称为V...，测电压是固定电流，名称是I...\n",
    "    VorI=0                 #测量变量1的固定电压为0 V\n",
    "    Comp=0.1                  #测量变量1的限流值\n",
    "    range='Auto'                #测量变量1的Range\n",
    "    Measurement_setup  += [Unit,VName,VorI,Comp,range] #打包测量变量，有几个打包几个\n",
    "\n",
    "\n",
    "    #print(Measurement_setup)\n",
    "    B1500a.timeout = 60000\n",
    "    B1500a.write('*RST')\n",
    "    B1500a.write('CN 1,2,3,4')\n",
    "    import B1500\n",
    "    res = B1500.IV_sweept(B1500a,VAR_setup,Measurement_setup,ADC=ADC,t_hold=t_hold,s_delay=s_delay,t_delay=t_delay)#AIT 1,2,1 20ms 1,1,125 10ms\n",
    "\n",
    "    import pandas\n",
    "    df = pandas.DataFrame(res[1:],columns=['GateV','GateI','DrainV','DrainI','SourceV','SourceI'],dtype=float)\n",
    "    B1500a.close()\n",
    "    rm.close()\n",
    "    return df\n",
    "from matplotlib import pyplot as plt \n",
    "import numpy as np\n",
    "\n",
    "def timemap(tstr):\n",
    "    l = tstr.split(',')\n",
    "    if l[1]=='1':\n",
    "        return str(0.08*int(l[2]))+'ms'\n",
    "    else:\n",
    "        return str(20*int(l[2]))+'ms'\n",
    "\n",
    "n=1\n",
    "for i in range(n):\n",
    "    for t_hold in [0,1,2,5]:\n",
    "        for s_delay in [0,0.001,0.010,0.020,0.050]:\n",
    "            for tp in ['P','N']:\n",
    "                #True False\n",
    "                df = transCurve(tp,ADC='AIT 1,2,1',t_hold=t_hold,s_delay=s_delay)\n",
    "                plt.plot(df['GateV'],abs(df['SourceI']),label=f'{tp}SourceI')\n",
    "                #plt.plot(df['GateV'],abs(df['DrainI']),label=f'{tp}DrainI')\n",
    "                plt.yscale('log')\n",
    "                from datetime import datetime\n",
    "                tStamp = datetime.strftime(datetime.now(),\"%Y%m%d_%H%M%S\")\n",
    "                df.to_excel(f\"./result/{tp}MOS-SINV1-{tStamp}-{t_hold}s-{s_delay*1000}ms.xlsx\",sheet_name='Data')\n",
    "                print(f\"\\r{tp}MOS-DIE-{tStamp}-{t_hold}s-{s_delay*1000}ms\",end='')\n",
    "\n",
    "#plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#b1500a smu\n",
    "def inverter():\n",
    "    PROBER = \"TCPIP0::192.168.0.2::800::SOCKET\"\n",
    "    SMU = \"GPIB0::17::INSTR\"\n",
    "    SWITCH = \"GPIB0::22::INSTR\"\n",
    "\n",
    "    import pyvisa\n",
    "    rm = pyvisa.ResourceManager()\n",
    "\n",
    "    B1500a = rm.open_resource(SMU)\n",
    "    B1500a.write('*RST')\n",
    "    B1500a.write('CN')\n",
    "\n",
    "    #--------------------IV_Sweep函数测试参数示例（双变量扫描）------------------#\n",
    "    Unit1='3'                     #扫描变量1对应的物理端口为4\n",
    "    VName1='VVin'                   #扫描变量1的名字为VD，注意电压模式的端口命名为V....,电流模式端口命名为I...\n",
    "    Direction1='Single Linear'    #扫描变量1的方向为Double，并且加电压模式为Linear（更多模式见34）\n",
    "    Start1=0                   #扫描变量1的起始电压为-3 V\n",
    "    end1=2.0                      #扫描变量1的终止电压为3 V\n",
    "    nop1=101                      #扫描变量1的点数目为201（Double的话，实际数据点为201*2）\n",
    "    Comp1=1e-2                  #扫描变量1的限流值\n",
    "    range1='Auto'         #扫描变量1的测量Range\n",
    "\n",
    "    VAR_setup=[Unit1,VName1,Direction1,Start1,end1,nop1,Comp1,range1] #打包扫描变量，如果单变量扫描，不用第二行\n",
    "\n",
    "    Measurement_setup = []\n",
    "    Unit='1'                    #测量变量1的物理端口为\n",
    "    VName='VVdd'                  #测量变量1的名称，注意测电流是固定电压名称为V...，测电压是固定电流，名称是I...\n",
    "    VorI=2.0                 #测量变量1的固定电压为0 V\n",
    "    Comp=1e-2                  #测量变量1的限流值\n",
    "    range='Auto'                #测量变量1的Range\n",
    "    Measurement_setup  += [Unit,VName,VorI,Comp,range] #打包测量变量，有几个打包几个\n",
    "\n",
    "    Unit='4'                    #测量变量1的物理端口为\n",
    "    VName='VGND'                  #测量变量1的名称，注意测电流是固定电压名称为V...，测电压是固定电流，名称是I...\n",
    "    VorI=0.0                 #测量变量1的固定电压为0 V\n",
    "    Comp=1e-2                  #测量变量1的限流值\n",
    "    range='Auto'                #测量变量1的Range\n",
    "    Measurement_setup  += [Unit,VName,VorI,Comp,range] #打包测量变量，有几个打包几个\n",
    "\n",
    "    Unit='2'                    #测量变量1的物理端口为\n",
    "    VName='IVout'                  #测量变量1的名称，注意测电流是固定电压名称为V...，测电压是固定电流，名称是I...\n",
    "    VorI=0.0                 #测量变量1的固定电压为0 V\n",
    "    Comp=5                  #测量变量1的限流值\n",
    "    range='Auto'                #测量变量1的Range\n",
    "    Measurement_setup  += [Unit,VName,VorI,Comp,range] #打包测量变量，有几个打包几个\n",
    "    #print(Measurement_setup)\n",
    "    B1500a.timeout = 60000\n",
    "    B1500a.write('*RST')\n",
    "    B1500a.write('CN 1,2,3,4')\n",
    "    import B1500\n",
    "    res = B1500.IV_sweept(B1500a,VAR_setup,Measurement_setup)\n",
    "\n",
    "    import pandas\n",
    "    df = pandas.DataFrame(res[1:],columns=['Vin','Iin','Vdd','Idd','VGND','IGND',\"Iout\",'Vout'],dtype=float)\n",
    "    B1500a.close()\n",
    "    return df\n",
    "df = inverter()\n",
    "from matplotlib import pyplot as plt \n",
    "plt.plot(df['Vin'],df['Vout'])\n",
    "plt.show()\n",
    "\n",
    "from datetime import datetime\n",
    "tStamp = datetime.strftime(datetime.now(),\"%Y%m%d_%H%M%S\")\n",
    "df.to_excel(f\"./result/inverter_{tStamp}.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     GateV         GateI  DrainV    DrainI  SourceV       SourceI\n",
      "0   -0.500 -7.580000e-10     2.0  0.000102      0.0  2.000000e-11\n",
      "1   -0.475 -6.130000e-10     2.0  0.000102      0.0  2.100000e-11\n",
      "2   -0.450 -7.160000e-10     2.0  0.000102      0.0 -8.300000e-11\n",
      "3   -0.425 -6.970000e-10     2.0  0.000102      0.0  2.500000e-11\n",
      "4   -0.400 -6.870000e-10     2.0  0.000102      0.0 -4.600000e-11\n",
      "..     ...           ...     ...       ...      ...           ...\n",
      "96   1.900  1.300000e-10     2.0  0.033238      0.0 -3.317800e-02\n",
      "97   1.925  2.210000e-10     2.0  0.035030      0.0 -3.496000e-02\n",
      "98   1.950  1.730000e-10     2.0  0.036751      0.0 -3.664500e-02\n",
      "99   1.975  2.530000e-10     2.0  0.038498      0.0 -3.842800e-02\n",
      "100  2.000  2.670000e-10     2.0  0.040341      0.0 -4.032100e-02\n",
      "\n",
      "[101 rows x 6 columns]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(df)\n",
    "from matplotlib import pyplot as plt \n",
    "plt.plot(df['GateV'],abs(df['DrainI']),label=f'{tp}SourceI')\n",
    "plt.yscale('log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Vin           Iin  Vdd           Idd  VGND          IGND  Iout     Vout\n",
      "0    0.00  1.565000e-09  2.0  4.623000e-09   0.0  6.283000e-09   0.0  2.00012\n",
      "1    0.02 -7.927000e-09  2.0  1.675400e-08   0.0  5.921000e-09   0.0  2.00008\n",
      "2    0.04 -5.472000e-09  2.0  1.528900e-08   0.0 -2.040000e-10   0.0  2.00004\n",
      "3    0.06  2.283000e-09  2.0  9.957000e-09   0.0 -7.473000e-09   0.0  2.00008\n",
      "4    0.08  1.990000e-09  2.0 -8.324000e-09   0.0  6.541000e-09   0.0  2.00008\n",
      "..    ...           ...  ...           ...   ...           ...   ...      ...\n",
      "96   1.92  1.110100e-09  2.0 -4.850000e-09   0.0  1.212800e-08   0.0  0.00004\n",
      "97   1.94 -6.031400e-09  2.0  9.402000e-09   0.0 -1.007100e-08   0.0  0.00002\n",
      "98   1.96 -3.475700e-09  2.0 -6.011000e-09   0.0  1.324800e-08   0.0  0.00002\n",
      "99   1.98 -6.848900e-09  2.0  7.620000e-09   0.0 -1.625500e-08   0.0  0.00004\n",
      "100  2.00 -2.925000e-10  2.0 -6.336000e-09   0.0  1.370100e-08   0.0  0.00003\n",
      "\n",
      "[101 rows x 8 columns]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas\n",
    "df = pandas.DataFrame(res[1:],columns=['Vin','Iin','Vdd','Idd','VGND','IGND',\"Iout\",'Vout'],dtype=float)\n",
    "\n",
    "from matplotlib import pyplot as plt \n",
    "plt.plot(df['Vin'],df['Vout'])\n",
    "plt.show()\n",
    "\n",
    "from datetime import datetime\n",
    "tStamp = datetime.strftime(datetime.now(),\"%Y%m%d_%H%M%S\")\n",
    "df.to_excel(f\"./result/inverter_{tStamp}.xlsx\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
